Browsing by Author "Hasan, Mahmudul"
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- ItemOpen AccessBalanced Multiresolution for Symmetric/Antisymmetric Filters(2014-05-13) Hasan, Mahmudul; Samavati, Faramarz; Costa Sousa, MarioGiven a set of symmetric/antisymmetric filter vectors containing only regular multiresolution filters, the method we present in this article can establish a balanced multiresolution scheme for images, allowing their balanced decomposition and subsequent perfect reconstruction without the use of any extraordinary boundary filters. We define balanced multiresolution such that it allows balanced decomposition i.e. decomposition of a high-resolution image into a low-resolution image and corresponding details of equal size. Such a balanced decomposition makes on-demand reconstruction of regions of interest efficient in both computational load and implementation aspects. We find this balanced decomposition and perfect reconstruction based on an appropriate combination of symmetric/antisymmetric extensions near the image and detail boundaries. In our method, exploiting such extensions correlates to performing sample (pixel/voxel) split operations. Our general approach is demonstrated for some commonly used symmetric /antisymmetric multiresolution filters. We also show the application of such a balanced multiresolution scheme in real-time focus+context visualization.
- ItemOpen AccessBalanced Multiresolution in Multilevel Focus+Context Visualization(2018-08-22) Hasan, Mahmudul; Samavati, Faramarz; Costa Sousa, Mário; Mudur, Sudhir Pandurang; Gavrilova, Marina L.; Jacob, Christian J.; Katz, LarryGiven a set of symmetric/antisymmetric filter vectors containing only regular multiresolution filters, the method we present in this thesis can establish a balanced multiresolution (BMR) scheme for images, allowing their balanced decomposition and subsequent perfect reconstruction without the use of any extraordinary boundary filters. We define balanced multiresolution such that it allows balanced decomposition i.e. decomposition of a high-resolution image into a low-resolution image and corresponding details of equal size. Several applications of such a decomposition result in a balanced wavelet transform (BWT) that makes on-demand reconstruction of regions of interest (ROIs) efficient in both computational load and implementation aspects. We find such decomposition and perfect reconstruction based on an appropriate combination of symmetric/antisymmetric extensions near the image and detail boundaries. In our method, exploiting such extensions correlates to performing sample (pixel/voxel) split operations. We demonstrate our general approach for some commonly used symmetric/antisymmetric multiresolution filters. We also show the application of such a balanced multiresolution scheme in constructing an interactive multilevel focus+context visualization framework for the navigation and exploration of large-scale 2D and 3D images. Typically, the given filters are floating-point values, so our BWTs reversibly map integers to floating-point i.e. real values. We extend our balanced multiresolution framework further to construct reversible integer-to-integer BWTs from a given symmetric/antisymmetric decomposition filter vector of width less or equal to four. In our approach, we adjust the linear combination of fine samples suggested by the given decomposition vector using optimal sample split operations in combination with a rounding operation. Such adjustments translate an affine integer combination of fine samples to obtain an integer coarse sample, which closely approximates the floating-point coarse sample suggested by the given decomposition filter vector. The associated translation vectors give us the detail samples. Furthermore, when necessary, we construct every other detail sample differently in order to ensure local perfect reconstruction. Compared to their integer-to-real counterparts, the resulting reversible integer-to-integer BWTs occupy less memory, offer better compressibility, and do not require sample quantization for rendering purposes.
- ItemOpen AccessGeometric approaches to path optimization and collision avoidance(2009) Hasan, Mahmudul; Gavrilova, Marina L.
- ItemOpen AccessInteractive Data Styling and Multifocal Visualization for a View-Aware Digital Earth(2016-10-21) Sherlock, Mark; Hasan, Mahmudul; Samavati, FaramarzA Discrete Global Grid System (DGGS) is a powerful tool for creating the discrete reference models that support geospatial dataset integration, organization, processing, and visualization in a Digital Earth (DE) application. However, the growing size and scale of geospatial datasets present significant obstacles to the interactivity and accessibility of geospatial visualizations. To address this challenge, we present a portable DGGS that runs in web browsers on a client device and efficiently communicates with a server-side DGGS. In our method, the client-side is responsible for triggering queries for missing data, managing the viewing area, and rendering various styles and effects. The server is responsible for generating data representations for DGGS cells in response to queries from clients. The resulting system is capable of interactively displaying multiple simultaneous viewpoints which enable support for multilevel focus+context visualization on the globe. We also provide several real-time data styling techniques that are designed to work efficiently on both the client and server. These methods help make DE more accessible and informative than ever before.